1. Field of Invention
The adjacent connected nodes determined in step S150 are then added to the set of active nodes in step S160. In various exemplary embodiments according to this invention, less interesting Degree-Of-Interest values may be associated with increasing negative numbers. The focus of attention or most interesting node is typically associated with a most interesting Degree-Of-Interest value of zero. However, it will be apparent that any ordering of Degree-Of-Interest values may be used without departing from the scope of this invention. After the set of active nodes have been determined, control continues to step S170.
2. Description of Related Art
The request from the internet enabled personal computer 300 is received by the input/output circuit or routine 10 of the second user interest estimation manager or system 101. The processor 21 of the user interest estimation manager or system 100 activates the input/output circuit 11 to retrieve the documents 1000–1002 from the information repository 200.
The processor 21 determines the graph structure to be displayed in the visualization. The focus of attention determination circuit or routine 41 is then activated to determine interesting nodes based on the user's focus of the attention. For example, a user selection of a specific node with cursor, eye and/or head tracking, gesture tracking and the like may be used to determine the interesting nodes. However, it should be apparent that any known or later developed method of determining a focus of attention may also be used in the practice of this invention. The processor 21 then adds the determined focus of attention nodes to the set of active nodes as interesting nodes.
For example, determining Degree-Of-Interest values using Furnas' conventional techniques typically results in run times proportional to the size of the graph structure. Thus, since these conventional visualization systems require time proportional to the number of nodes in the graph structure, they do not scale well. As the size of the information structure to be visualized increases, delays in presentation and interaction are introduced.
The delays may also affect the usability of the dynamic interactive visualization systems. For example, Card et al., notes in The Psychology of Human-Computer Interaction”, Hillsdale, N.J., Lawrence Erlbaum, 1983, herein incorporated by reference in its entirety, that delays of more than a 100 milliseconds are perceived by the human visual system and tend to interrupt the user. Thus, to avoid perceptible presentation and interaction delays, dynamic interactive visualization systems must render the complete visualization within a smaller 100 millisecond window.
These constraints tend to limit the deployment of visualization systems. Moreover, these constraints also limit the size of the graph structures that can be dynamically visualized. Some researchers have attempted to optimize the Degree-Of-Interest function to address these limitations. For example, in “Generalized fisheye views” in Proceedings of CHI'86, Human Factors in Computer Systems, 1986, herein incorporated by reference in its entirety, G. W. Furnas notes that nodes to be updated lie within a subtree rooted at the nearest common ancestor or the previous and current focus of attention. Certain descendant branches of the subtree may also be pruned. However, the resultant subtree may still be arbitrarily large. Also, these techniques depend on features associated with the specific Degree-Of-Interest function used. Thus, separate optimizations for each Degree-Of-Interest function are typically necessary.